Ryuto Shigenobu

Optimal Operation and Management for Smart Grid Subsumed High Penetration of Renewable Energy, Electric Vehicle, and Battery Energy Storage System

Abstract Distributed generators (DG) and renewable energy sources have been attracting special attention in distribution systems in all over the world. Renewable energies, such as photovoltaic (PV) and wind turbine generators are considered as green energy. However, a large amount of DG penetration causes voltage deviation beyond the statutory range and reverse power flow at interconnection points in the distribution system. If excessive voltage deviation occurs, consumer’s electric devices might break and reverse power flow will also has a negative impact on the transmission system. Thus, mass interconnections of DGs has an adverse effect on both of the utility and the customer. Therefore, reactive power control method is proposed previous research by using inverters attached DGs for prevent voltage deviations. Moreover, battery energy storage system (BESS) is also proposed for resolve reverse power flow. In addition, it is possible to supply high quality power for managing DGs and BESSs. Therefore, this paper proposes a method to maintain voltage, active power, and reactive power flow at interconnection points by using cooperative controlled of PVs, house BESSs, EVs, large BESSs, and existing voltage control devices. This paper not only protect distribution system, but also attain distribution loss reduction and effectivity management of control devices. Therefore mentioned control objectives are formulated as an optimization problem that is solved by using the Particle Swarm Optimization (PSO) algorithm. Modified scheduling method is proposed in order to improve convergence probability of scheduling scheme. The effectiveness of the proposed method is verified by case studies results and by using numerical simulations in MATLAB®.

Multi-Objective Optimal Operation for Transmission Systems Considering Voltage Stability

Abstract Due to the liberalization of electric power market, many power producers are entering into the power market. Most of electric power company have been introduced renewable energies that might increase the power system uncertainty. Therefore, it is expected that rise might the likelihood of voltage instability and voltage collapse. In addition, fluctuations in supply and demand are increased by the introduction of a renewable energies. However, by using the Energy storage systems (ESS), the power fluctuations can be reduced. On account of this, we suggest the optimal operation method of the generator and the ESS by considering the voltage stability in this paper. The effectiveness of the proposed method is verified by simulation results in the Matlab/simulink.

Optimal operation method with fuel cells in plural regional power systems

Since the great east Japan earthquake, photovoltaic (PV) and wind generator (WG) are introduced actively as a solution regarding shortage of electrical power with the stopping of nuclear power plants. Renewable energy source such as PV generator and WG contribute for prevention of global warming because these energy dose not use fossil fuels and it can reduce carbon dioxide emissions. However, it is difficult to predict renewable energy facility output because this output depends on weather conditions. It may reduce power quality. As a countermeasure of the fluctuation of power output, battery energy storage system (BESS) is introduced into power system. BESS is very effective facility because it can compensate the surplus and shortage power by charging and discharging. However, it is necessary to investigate the high cost for installation of large BESS. Thus, the fuel cell and the hydrogen generation apparatus are installed in the proposed scheduling method. The fuel cell can absorb surplus power, and surplus power is converted into hydrogen and it is accumulated by hydrogen storage device. Furthermore, it is possible to generate power easily by using the hydrogen which is stored in the fuel cell, when the shortage power occurs. As a consequence, the high-efficiency operation plan is determined to reduce the operation cost which had been accomplished, by introducing the fuel cell and the hydrogen generation apparatus.

Suppression of power system voltage and frequency fluctuations by decentralized controllable loads

A recent trend of the power system is the ever increasing number of distributed generators (DGs) utilizing renewable energy sources, which have output powers that fluctuate due to unpredictable weather and ambient conditions. This causes fluctuations in system frequency and bus voltages, resulting in poor quality power, higher prices for electricity, and increased chances of reverse power flow and voltage collapse. In order to allow higher levels of DG penetration, methods of reducing the effects of fluctuations must be implemented. This paper proposes a method to mitigate these fluctuations using controllable loads such as heat pump water heaters (HPs) and battery storage systems. The HPs are controlled using a decentralized bang-bang (on/off) control based on the cumulative distribution of water temperature of HPs in the local area and the local frequency. Battery systems are controlled using a smart frequency and voltage droop characteristics based control. The decentralized bang-bang control mitigates local frequency fluctuations by increasing active power consumption to lower frequency as well as decreasing active power consumption to increase the frequency. The smart droop characteristics based control applies a commonly used droop characteristics control to voltage and frequency; however, the control system monitors the state of charge (SOC) of the battery system and takes appropriate actions to prevent the SOC from reaching a critical level. The results of simulations show that fluctuations in frequency and bus voltage are mitigated by the application of the proposed control methodologies without adversely affecting the comfort level of consumers.

Multi-objective optimization of auto-tap-changer pole transformer considering optimum placement in distribution systems

This paper proposes the application of multi-objective optimization to tap changing transformers in a distribution system. Conventional electrical power systems do not consider reverse power flow, in which the power flows toward the power system in distribution systems. When large quantities of distributed generators (DGs) are introduced into a distribution system they can cause voltage deviations beyond the statutory range, and can reverse flow toward the substation transformer. Consequently, this cause faults in electricity devices and even lead to a massive blackout. This is an important issue within the distribution system. To resolve voltage deviation problems it is necessary to consider some trade-offs. However, there is not much research adapting multi-objective optimization for use in the distribution system. Therefore this paper provides a method of multi-objective optimization in order to minimize voltage deviation while simultaneously minimizing the number of introduced voltage control devices and finding an optimum placement of those voltage control devices. Moreover, an optimum scheduling of the distribution system is adopted.

Optimal demand response considering the optimal power flow in electricity market

Distribution generator (DGs) using renewable energy sources (RESs) has introduced in the distribution system from economy and the environment issues. However, high DGs penetration in distribution system cause voltage deviation beyond the statutory range and also reverse power flow toward the substation and generator. It is necessary to introduce the real time pricing (RTP) by distribution company (DisCo) for improve the above problems and load leveling. This paper propose a method that is demand response (DR) by a RTP in electricity market and provide reactive power incentive to cooperative customer for maintain distribution voltage within the proper range. This paper shows the effectiveness of RTP and reactive power incentive by simulation for DisCo and customer profit.

New optimization method considering combinatorial and multi-objective optimization problem for distribution systems

This paper proposes a new optimization method for distribution system, that method includes combinational problem (CP) as factor in multi-objective optimization problem (MOOP). Increasing load demands and deep penetration of distributed generators (DGs) using renewable energy sources (RESs) has been a cause of concern to protect the smart grid. System. As a t, it causes voltage deviation and reverses power flow. In order to solve these problem, protection devices have to be installed in distribution system. However, it is necessary to consider multi objects to realize safety system, generally these objects are also conflicting with each other. Moreover, it is also important problem to calculate operating cost and finding optimal placement of control devices. This proposed method provides an application for distribution system.

Modeling method of controllable loads with decentralized and PID+DD control systems for use in electric power transmission systems

Distributed generation based on renewable energy sources (RES) continues to increase in electric power system penetration. In order to mitigate stability issues caused by high penetration of these weather-dependent systems, some type of control is necessary. This paper proposes a method to model heat pump water heaters (HPs) and battery systems for a coordinated control strategy, which can be used to suppress perturbations caused by renewable energy source based distributed generators in high-voltage transmission systems. The loads are controlled with decentralized and autonomous control techniques in order to mitigate problems caused by high penetration of RES based distributed generators. The models of controllable loads have been simplified such that simulations of these highly nonlinear systems may be run in acceptable times. The effectiveness of the proposed control system is validated by simulation results in MATLAB/Simulink™

Suppression of voltage and frequency fluctuations by PID+DD and decentralized control in transmission systems

Distributed generation based on renewable energy sources (RES) continues to increase in electric power system penetration. In order to mitigate stability issues caused by high penetration of these weather-dependent systems, some type of control is necessary. This paper proposes a coordinated control methodology for loads which can be used to suppress perturbations caused by DGs in high-voltage transmission systems. Battery systems and heat pump water heaters are used as controllable loads with decentralized and autonomous control techniques in order to mitigate problems caused by high penetration of RES based distributed generators. The effectiveness of the proposed control system is validated by simulation results in MATLAB/Simulink™.

Multi-objective optimization approach for SVRs annual optimal operation and optimal placement

This paper proposes an application of multi objective optimization method in a smart grid. Recently, smart gird problems has become more diversified and complex which cannot be solved by single objective optimization method. Technical, economical, and placement problems of control devices should also be considered as required. The technical and economical problems are treated as ordinal multi objective optimization problem, in addition, with the operating schedule of control devices. The placement problem can be solved by using concept of combinational optimization. Therefore, this paper provides an optimization method, which simultaneously considers both multi objects and combinational problem. The handling method for combinational problems and two fold diversity in pareto optimal solutions are also provided. Finally, an index is provided from which solution can be selected by system designer and operator. This method enables to calculate annual simulation, which helps to solve optimal placement and scheduling problem throughout annual simulation.